U.S. patent application number 11/490540 was filed with the patent office on 2007-02-22 for storing and recalling information to augment human memories.
This patent application is currently assigned to Tangis Corporation. Invention is credited to Kenneth H. III Abbott, Dan Newell, James O. Robarts.
Application Number | 20070043459 11/490540 |
Document ID | / |
Family ID | 23844784 |
Filed Date | 2007-02-22 |
United States Patent
Application |
20070043459 |
Kind Code |
A1 |
Abbott; Kenneth H. III ; et
al. |
February 22, 2007 |
Storing and recalling information to augment human memories
Abstract
A system for computer-based storing of information about a
current state so that later recall of the information can augment
human memories. In particular, when information about a current
event of interest is to be stored, a variety of current state
information of different types (e.g., video, audio, and textual
information) about the environment and about a user can be acquired
via sensors and other input devices. The variety of state
information can then be associated together as a group and stored
for later retrieval. Other information can also be associated with
the group, such as one or more recall tags that facilitate later
retrieval of the group, or one or more annotations to provide
contextual information when the other state information is later
retrieved and presented to the user. When information about a past
event is to be recalled, one or more identifying recall tags can be
received that are used to identify one or more state information
groups that match the identifying tags. Some or all of the
previously-acquired state information for the identified state
information groups can then be presented to the user on appropriate
output devices. Other information, such as annotations, can also be
presented to the user in order to describe the state information
and thus assist the user's recollection of the previous state when
the information was stored.
Inventors: |
Abbott; Kenneth H. III;
(Kirkland, WA) ; Newell; Dan; (Seattle, WA)
; Robarts; James O.; (Redmond, WA) |
Correspondence
Address: |
SEED INTELLECTUAL PROPERTY LAW GROUP PLLC
701 FIFTH AVE
SUITE 5400
SEATTLE
WA
98104
US
|
Assignee: |
Tangis Corporation
Medina
WA
|
Family ID: |
23844784 |
Appl. No.: |
11/490540 |
Filed: |
July 19, 2006 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
10371436 |
Feb 21, 2003 |
7155456 |
|
|
11490540 |
Jul 19, 2006 |
|
|
|
09876814 |
Jun 6, 2001 |
6549915 |
|
|
10371436 |
Feb 21, 2003 |
|
|
|
09464659 |
Dec 15, 1999 |
6513046 |
|
|
09876814 |
Jun 6, 2001 |
|
|
|
Current U.S.
Class: |
700/94 ;
707/E17.143 |
Current CPC
Class: |
G06F 16/40 20190101;
Y10S 707/99945 20130101; Y10S 707/99948 20130101; G06F 16/907
20190101 |
Class at
Publication: |
700/094 |
International
Class: |
G06F 17/00 20060101
G06F017/00 |
Claims
1-75. (canceled)
76. A method in a computer for augmenting a memory of a user, the
computer having a plurality of stored groups of information such
that each stored group of information describes an environment and
includes at least one tag and descriptive information about the
environment and recorded information for the environment, the
method comprising: receiving an indication of a tag; determining
whether one of the stored groups of information has a tag matching
the indicated tag; and when one of the stored groups of information
is determined to have a matching tag, augmenting the memory of the
user about the environment by, presenting to the user the recorded
information from the determined group of information; and
presenting to the user the descriptive information from the
determined group of information.
77. The method of claim 76 including, after the determining,
sending the determined group to another module.
78. The method of claim 76 wherein the indication of the tag is
received from the user.
79. The method of claim 76 wherein the indication of the tag is
generated automatically without human intervention.
80. The method of claim 76 including, before the receiving of the
indication of the tag, generating a stored group of information
about a current state of the environment in response to a received
indication.
81. The method of claim 76 wherein the indicated tag is textual
information.
82. The method of claim 76 wherein the indicated tag is audio
information.
83. The method of claim 76 wherein the indicated tag is video
information.
84. The method of claim 76 wherein the determined one group of
information includes sensed information about a state of the user
at a previous time when the recorded information for the determined
group was recorded.
85. The method of claim 76 including, before the determining of
whether one of the stored groups of information has a tag matching
the indicated tag, receiving one or more indications of one or more
additional tags, and wherein the determining includes matching at
least one of the additional indicated tags to at least one of the
stored groups of information.
86. The method of claim 85 wherein at least one of the stored
groups of information includes multiple tags, and wherein the
determining further includes identifying one of the stored groups
of information whose multiple tags match the indicated tag and the
additional indicated tags.
87. The method of claim 76 including receiving one or more
indications of additional tags.
88. The method of claim 76 including, after the determining,
sending information from the determined group to another
module.
89. A computer-implemented method for augmenting a memory of a user
about an environment, the method comprising: storing information
about a current state of the environment by, recording information
regarding the environment; receiving an indication of a tag related
to the environment; receiving an indication of descriptive
information about the environment; and associating the indicated
tag and the indicated descriptive information with the recorded
environment information, so that if the tag is later supplied, the
recorded environment information and the descriptive information
can be presented to augment the memory of the user of the
environment.
90. The method of claim 89 wherein the environment is external to
the user, and wherein the recorded information is obtained with at
least one input device of the computer.
91. The method of claim 89 wherein the storing of the information
about the current state is in response to an indication from the
user.
92. The method of claim 89 wherein the storing of the information
about the current state is in response to an indication generated
automatically without human intervention.
93. The method of claim 89 including, after the storing of the
information about the current state, presenting to the user the
stored information about the current state in response to a
received indication matching the tag.
94. A computer-readable medium whose contents cause a computer to
augment a memory of a user, the computer having access to multiple
stored groups of information that each has at least one associated
tag and associated descriptive information about an environment and
associated recorded information for that environment, by performing
a method comprising: receiving an indication of a tag; determining
one of the stored groups of information that has an associated tag
matching the indicated tag; and augmenting the memory of the user
about an environment by presenting information for the environment
to the user that is associated with the determined group of
information, the presented information including the recorded
information for the environment and the descriptive information
about the environment.
95. A computer-readable medium whose contents cause a computer to
augment a memory of a user about an environment, by performing a
method comprising: storing information about a current state of the
environment by, recording information regarding the environment;
receiving an indication of a tag related to the environment;
receiving an indication of descriptive information about the
environment; and associating the indicated tag and the indicated
descriptive information with the recorded environment information,
so that the recorded environment information and the descriptive
information can later be presented to augment the memory of the
user of the environment.
Description
TECHNICAL FIELD
[0001] The present invention relates generally to computer-assisted
information management, and more particularly to computer-based
storing of information about a current state to facilitate later
recall.
BACKGROUND OF THE INVENTION
[0002] As daily life becomes even more complex, people increasingly
need to effectively manage a wide variety of types of information.
In particular, people need the capability to store a broad range of
types of information in such a manner that the information is
easily accessible when needed.
[0003] Unfortunately, people are frequently unable to remember some
types of information without assistance. For example, some types of
information need to be remembered frequently, but a particular
instance of the information need be retained for only a limited
time (e.g., the location where the car keys were last left or the
location in which the car was parked this morning). For such types
of information, a typical human often remembers the information
when it is later needed, but at least occasionally will be unable
to remember the information. Other types of information may be
difficult to remember due to the volume of information or the
circumstances under which it is acquired. For example, after
meeting another person, many people can remember the name and face
of the person, as well as other related information (e.g., a phone
number or birth month). However, after meeting a large number of
people at a party, a typical human remembers such information for
at most a small number of the people. In other situations, people
take video recordings (e.g., a still picture or a stream of video
frames) or audio recordings of information which they have
perceived but cannot fully remember without assistance (e.g., of a
song or of beautiful scenery). For yet other types of information,
the information may be sufficiently complex or may be needed so
infrequently so as to prevent mental recall (e.g., credit card and
frequent flier numbers, or a rarely-used numerical value such as
pi).
[0004] Due to people's inability to remember information, a variety
of techniques and devices have been developed to assist people in
storing and recalling information. For example, some people carry
portable audio recording devices (e.g., a DICTAPHONE.RTM. device)
on which audible information can be quickly stored, while others
textually store information of interest on a portable medium (e.g.,
on a hand-held computer, on a paper-based DAY-TIMER.RTM. calendar,
on POST-IT.RTM. notes, etc.). Some people may even carry video
recording devices (e.g., a camera or camcorder) to record scenes or
events of interest.
[0005] Unfortunately, these existing techniques and devices for
storing and recalling information have various problems. Consider,
for example, the situation in which a person encounters a large
number of people at a party and would like to store a variety of
information about each person, such as their name, face, and
telephone number. Devices able to record only a single type of
information, such as audio, video, or textual information, would be
unable to store some of the desired information about the people
encountered. If different devices were used to each store one type
of information, it would be difficult to associate the different
stored information and quickly retrieve the disparate pieces of
information when needed. In addition, while storage devices having
a linear storage mechanism (including most audio recording devices
and camcorders) can quickly store large amounts of information,
this form of storage mechanism makes retrieval of desired
information (e.g., Bob's telephone number and face) difficult
because the only available means of searching is sequential and not
indexed. Moreover, each of these techniques and devices store
information only at the explicit direction of a user. Thus, if a
user does not recognize the need to store information while it is
available, these techniques and devices will not allow the
information to be later recalled. For these and a variety of other
reasons, existing techniques and devices do not fully meet the
needs for storing and recalling a variety of types of
information.
SUMMARY OF THE INVENTION
[0006] Some embodiments of the present invention provide a method
and system for computer-based storing of information about a
current state so that later recall of the information can augment
human memories. In particular, when information about a current
event of interest is to be stored, a variety of current state
information of different types (e.g., video, audio, and textual
information) about the environment, a user, and the computer can be
acquired via sensors and other input devices. The variety of state
information can then be associated together as a group and stored
for later retrieval. Other information can also be associated with
the group, such as one or more recall tags that facilitate later
retrieval of the group, or one or more annotations to provide
contextual information when the other state information is later
retrieved and presented to the user. When information about a past
event is to be recalled, one or more identifying recall tags can be
received that are used to identify one or more state information
groups that match the identifying tags. Some or all of the
previously-acquired state information for the identified state
information groups can then be presented to the user on appropriate
output devices. Other information, such as annotations, can also be
presented to the user in order to describe the state information
and thus assist the user's recollection of the previous state when
the information was stored.
[0007] In one embodiment, a computer system has input devices
capable of recording audio and video information and has output
devices capable of presenting audio and video information. In this
embodiment, a method for augmenting the memory of a user of the
computer system involves receiving from the user a plurality of
indications each indicating to store an augmented memory. An
augmented memory is then stored for each of the plurality of
received indications by recording indicated video information,
recording from the user at least one audio recall tag related to a
subject of the recorded video information, recording from the user
at least one audio annotation providing descriptive information
about the recorded video information, and associating the recorded
video information, audio recall tag, and audio annotation as the
stored augmented memory. When the user indicates that one of the
stored augmented memories is to be recalled, a stored augmented
memory is recalled by receiving from the user an indication of a
subject, comparing the indicated subject to the recall tags of the
stored augmented memories, and when the indicated subject matches a
recall tag of one of the stored augmented memories, presenting to
the user the recorded video information associated with the matched
recall tag and presenting to the user the recorded audio annotation
associated with the matched recall tag. Thus, the user can recall
the video and annotation information associated with a stored
augmented memory of an indicated subject.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIG. 1 illustrates a user with an embodiment of the
Computer-Augmented Memory (CAM) system of the present
invention.
[0009] FIG. 2 illustrates a user wearing a body-mounted computer
executing an embodiment of the CAM system.
[0010] FIG. 3 is a block diagram illustrating the components of a
computer system executing an embodiment of the CAM system.
[0011] FIG. 4 is an exemplary flow diagram of an embodiment of the
User-Activated State Storage routine.
[0012] FIG. 5 is an exemplary flow diagram of an embodiment of the
User-Activated State Recall routine.
[0013] FIG. 6 is an exemplary flow diagram of an embodiment of the
Select Match Based On Additional Information subroutine.
[0014] FIG. 7 is a block diagram illustrating the contents and
information flow of an embodiment of a user modeling system.
[0015] FIG. 8 is an illustrative example of a model of a current
user condition.
[0016] FIG. 9 is an illustrative example of a User Characterization
Module.
[0017] FIG. 10 is an illustrative example of an Output Device
Selector Module.
[0018] FIG. 11 is an exemplary flow diagram of an embodiment of the
User Characterization routine.
[0019] FIG. 12 is an exemplary flow diagram of an embodiment of the
Characterize User subroutine.
[0020] FIG. 13 is an exemplary flow diagram of an embodiment of the
Output Device Selector routine.
[0021] FIG. 14 is an exemplary flow diagram of an embodiment of the
Format And Present Output Information subroutine.
[0022] FIG. 15 is an exemplary flow diagram of an embodiment of the
System-Activated State Storage routine.
[0023] FIG. 16 is an exemplary flow diagram of an embodiment of the
Determine Whether To Store Current State Of Input Devices, User
Model, And Computer Model subroutine.
[0024] FIG. 17 is an exemplary flow diagram of an embodiment of the
Create State Fragment subroutine.
[0025] FIGS. 18A and 18B are exemplary flow diagrams of an
embodiment of the System-Activated State Recall routine.
DETAILED DESCRIPTION OF THE INVENTION
[0026] The present invention provides a method and system for
computer-based storing of information about a current state so that
later recall of the information can augment human memories. In
particular, when information about a current event of interest is
to be stored, an embodiment of the Computer-Augmented Memory (CAM)
system acquires a variety of current state information of different
types (e.g., video, audio, and textual information) about the
environment, about a user of the CAM system, and about the CAM
system itself via internal and external sensors and other input
devices. The CAM system then associates the variety of state
information together as a group, and stores the group of state
information for later retrieval. In addition to the current state
information, the CAM system can also associate other information
with the group, such as one or more recall tags that facilitate
later retrieval of the group, or one or more annotations to provide
contextual information when the other state information is later
retrieved and presented to the user.
[0027] When information about a past event is to be recalled, an
embodiment of the CAM system receives one or more identifying
recall tags, identifies one or more state information groups that
match the identifying tags, and presents to the user on appropriate
output devices some or all of the previously-acquired state
information for the identified state information groups. Other
information, such as annotations, can also be presented to the user
in order to describe the state information and thus assist the
user's recollection of the previous state when the information was
stored.
[0028] In some embodiments, the CAM system stores and/or recalls
state information in response to explicit indications from the
user, while in other embodiments the CAM system stores and/or
recalls state information in response to indications generated by
the system. In order to produce system-generated indications, some
embodiments monitor the user and the surrounding environment, and
use the monitored information to maintain one or more models of
current conditions. These models enable the CAM system to determine
when events of interest are occurring so that state information can
be stored, as well as to determine when previously-stored state
information should be recalled and presented to the user.
[0029] Consider, for example, CAM system 100 being carried by user
110 in FIG. 1. In the exemplary embodiment illustrated in FIG. 1,
the CAM system has access to input sensor devices video camera 121
and microphone 124, and to a text input device 122 (e.g., a
keyboard or a hand-writing recognition device). The CAM system also
has access to the visual display 132 and speaker 134 output
devices. In some embodiments, the input and output devices may be
integrated together with the CAM system into a single device, while
in alternate embodiments the CAM system may be a separate device
that has the ability to accept input from and provide output to
(e.g., via physical or wireless connections) any of a variety of
devices which may be accessible (e.g., carried by the user or
located nearby in the environment).
[0030] In the example of FIG. 1, a variety of situations are
illustrated for which user 110 may wish to store state information
that can later augment his memory of the situation. For example,
upon encountering person 170 for the first time, the user may wish
to store a variety of information about the person for later
recollection. In particular, the user can use the video camera and
microphone to capture video and audio recordings of the encounter.
The user can also use the video camera to capture other current
state information about the environment which may assist in later
recollection about the encounter, such as a video image of the
location in which the encounter occurred. In addition, the user can
use the microphone to record dictated information about the person,
such as the person's name, address, e-mail address, phone number,
etc. The CAM system can then store this dictated information as an
audio recording, or can instead perform voice recognition on the
dictation in order to produce a textual version of the information.
Alternately, the user can provide some or all of the information
about the person to the CAM system directly as text via text input
device 121. In other embodiments, the user can provide information
to the CAM system via any other available input means, such as
transmitted information from a portable device (not shown) that the
person might be carrying (e.g., another CAM system). After
receiving and processing the various information about the
encounter with the person, the CAM system associates the various
received current state information together as a group, also
referred to as a state fragment, that can later be recalled and
made available to the user.
[0031] As another exemplary situation illustrated in FIG. 1, the
user may wish to store information about a location of an object,
such as the location where keys were last left or where a car is
parked. In particular, the user may wish to store information about
the location of object 150, such as after the user placed or saw
the object on table 160. The user can use the CAM system to store a
variety of information about the object, such as a picture of the
object on the table (e.g., if the table's appearance is
sufficiently unique to be identifying), a picture of the object
that includes the surrounding setting, or an audio recording of the
user describing the location of the object. Similarly, if the
object is located in an environment with distinctive sounds (e.g.,
the airport or the zoo), the user can generate an audio recording
of the surrounding environment that can later assist in identifying
the location. Alternately, if the CAM system has access to a GPS
receiver (not shown), the user can record GPS coordinates or an
address as information about the location. Information about the
location of the object can be stored in any form that is useful to
the user, whether relative to another object that is known to the
user (e.g., 10 meters north of Mom's favorite rose bush) or with an
absolute addressing scheme (e.g., GPS coordinates or a unique
street address). After receiving and processing the various
information about the object, the CAM system creates a state
fragment that includes the various received current state
information.
[0032] In a similar manner to the encounter with person 170 and the
location of object 150, the user may wish to store state
information about a variety of other types of situations, such as
about scenery 180 or an idea 190. Alternately, the user may wish to
store state information based on other situations (not shown), such
as based on information provided by the CAM system (e.g., a
reminder or a notification of received email) or on information
provided by another computer. For some types of situations, one or
more types of environment information may not be useful in
capturing the current state of the situation, such as video
information being generally not useful when capturing the current
state of an idea. Conversely, other types of information than
environment information and user-supplied information may be useful
in capturing the current state. For example, information generated
by the CAM system or other computer-generated information may be
useful (e.g., the current time, or inferred information about the
current situation). In addition, if information about the user can
be sensed or derived (e.g., body temperature or degree of
exhaustion), such user information can also be stored as part of
the state fragment. Those skilled in the art will appreciate that
the examples shown in FIG. 1 are for illustrative purposes only,
and that a variety of other types of situations and other types of
information can be stored by the CAM system.
[0033] The CAM system can also perform a variety of types of
additional processing for a state fragment being created. In
particular, the CAM system can associate one or more recall tags
with the state fragment that can assist in later retrieval of the
state fragment. For example, when encountering person 170, the user
may audibly or textually indicate that a name of the location
(e.g., the XYZ Conference or the ABC Church) and the person's name
should be recall tags for that state fragment. Alternately, if the
CAM system is able to determine that information about a person is
being stored, the CAM system can automatically determine to use the
person's name as a recall tag. In addition, the CAM system can
automatically associate other types of system-generated information
as recall tags with the state fragment, such as the current date
and time or an approximate age of the person based on automated
face recognition.
[0034] The CAM system can also categorize the state fragment in a
variety of ways that will assist later retrieval. For example, when
a state fragment is created for the encounter with person 170, the
user can explicitly indicate that the state fragment represents
information about a person or about an encounter with a person.
When the user later wants to recall information about the
encounter, only state fragments that are members of those
categories need be considered. More specific categories can also be
used for the state fragment, such as "Action Items," as well as
categories specific to the user, such as "Information From The XYZ
Conference" or "Members Of The ABC Church." A state fragment can be
associated with a number of different categories, and
system-generated categories can be used in the same manner as are
user-generated categories. If state fragment category information
is available when a state fragment is to be recalled, the category
information can be used in addition to or in lieu of recall tags
when identifying potentially matching state fragments.
[0035] The CAM system can also associate one or more annotations
with a state fragment in order to describe the state fragment or to
provide contextual information about the other state information in
the state fragment. For example, to accompany input device
information about person 170, the user may supply an annotation
such as "the vice-president of LMN Corporation" or "this was the
person I sat beside on the airplane," either audibly or via text.
In addition to being able to be presented concurrently with other
state fragment information, the annotations can also be used in
other ways. For example, when an attempt to recall a specific state
fragment produces multiple possible state fragments, presentation
of the annotations associated with the multiple state fragments may
provide a quick way to allow the user to select between the
possibilities. As with recall tags and categories, system-generated
annotations can be associated with state fragments in the same
manner as are user-generated annotations.
[0036] In addition to recall tags, categories, and annotations, the
CAM system can associate a variety of other types of information
with state fragments. For example, a retention time may be
associated with a state fragment, such as "forever," "5 hours,"
"until recalled 3 times," or "until another instance of this type
of information is stored." Similarly, an importance level may be
associated with a state fragment, such as for use when prioritizing
between multiple state fragments that are possible matches for a
state fragment being sought. An urgency level can also be
associated with a state fragment, such as to remind the user to
recall the state fragment when it is in a group of possible
matches, or to increase the likelihood that the system will
automatically determine to present the state fragment to the user.
Those skilled in the art will appreciate that these types of
information can be supplied by the user or can be system-generated,
and that a wide variety of other such types of information can be
associated with state fragments.
[0037] FIG. 2 illustrates an embodiment of the CAM system which
executes on a general-purpose body-mounted wearable computer 220
worn by user 110. Many wearable computers travel with the user,
such as being strapped or attached to a user's body or clothing or
being mounted in a holster. The wearable computer 220 has a variety
of user-worn user input devices including a microphone 124, a
hand-held flat panel display 230 with character recognition
capabilities, and various other user input devices 222. Similarly,
the computer has a variety of user-worn output devices that include
the hand-held flat panel display, an earpiece speaker 232, an
eyeglass-mounted display 234, and a tactile display 236. In
addition to the various user-worn user input devices, the computer
can also receive information from various user sensor input devices
226 and from environment sensor input devices 228, including video
camera 121. The CAM system can receive and process the various
input information received by the computer, and can present
information to the user on the various output devices accessible to
the computer. Thus, as the user moves about in various
environments, the CAM system receives various input information
from the input devices that can be stored in a state fragment when
appropriate.
[0038] In the current environment, computer 220 is accessible to a
computer 250 (e.g., by being in line-of-sight wireless proximity or
by being reachable via a long-distance communication device such as
a cellular phone) which also has a variety of input and output
devices. In the illustrated embodiment the computer 250 is
non-portable, although the body-mounted computer of the user can
similarly communicate with a variety of other types of computers,
including body-mounted computers of other users. The devices from
which the non-portable computer can directly receive information
include various user input devices 252 and various user sensor
input devices 256. The non-portable computer can output information
directly to a display 260, a speaker 262, an olfactory device 264,
and a printer 266. In the illustrated embodiment, the body-mounted
computer can communicate with the non-portable computer via a
wireless transmission medium. In this manner, the CAM system can
receive information from the user input devices 252 and the user
sensor devices 256 after the information has been transmitted to
the non-portable computer and then to the body-mounted computer.
Alternately, the body-mounted computer may be able to directly
communicate with the user input devices 252 and the user sensor
devices 256, as well as with other various remote environment
sensor input devices 258, without the intervention of the
non-portable computer 250. Similarly, the body-mounted computer may
be able to supply output information to the display 260, the
speaker 262, the olfactory device 264, and the printer 266, either
directly or via the non-portable computer, and directly to the
telephone 268. As the user moves out of range of the remote input
and output devices, the CAM system will be updated to reflect that
the remote devices are not currently available.
[0039] The various input devices allow the CAM system or another
system (not shown) executing on the computer 220 to monitor the
user and the environment and to maintain a model (not shown) of the
current conditions. Such a model can be used by the CAM system to
automatically determine when an event of interest is occurring for
which a state fragment should be created. For example, a user can
define a rule for the CAM system that indicates that whenever the
user's car is parked, a state fragment of the car location should
be created. Alternately, the CAM system can learn to automatically
store such information based on repeated user indications to store
a state fragment just after the car has been parked. If so, the CAM
system can automatically determine that the user's car has been
parked in a variety of ways, such as information received from an
on-board car computer, by image and audio processing that indicates
that a car is being exited, or by detection that the user has
stopped moving at speeds which exceed the user's ambulatory
capabilities.
[0040] In a similar manner, a model of the current conditions can
be used by the CAM system to automatically determine when a
previously stored state fragment should be presented to the user.
For example, the CAM system can detect that the user has
encountered for a second time a person (e.g., based on face or
voice recognition) for whom a state fragment was created of the
first encounter. In this situation, the CAM system can
unobtrusively prompt the user with information about the person
that was previously stored, such as the person's name or an
annotation indicating that the person is a potential business
customer. The automatic determination of when to create or recall a
state fragment will be discussed in greater detail later.
[0041] A model of the current conditions can include a variety of
condition variables that represent information about the user and
the user's environment at varying levels of abstraction. For
example, information about the user at a low level of abstraction
can include raw physiological data (e.g., heart rate and EKG) and
geographic information (e.g., location and speed), while higher
levels of abstraction may attempt to characterize or predict the
user's physical activity (e.g., jogging or talking on a phone),
emotional state (e.g., angry or puzzled), desired output behavior
for different types of information (e.g., to present private family
information so that it is perceivable only to myself and my family
members), and cognitive load (i.e., the amount of attention
required for the user's current activities). Background information
which changes rarely or not at all can also be included, such as
the user's age, gender and visual acuity. The model can similarly
hold environment information at a low level of abstraction, such as
air temperature or raw data from a motion sensor, or at higher
levels of abstraction, such as the number and identities of nearby
people, objects, and locations. The model of the current conditions
can additionally include information added explicitly from other
sources (e.g., application programs), as well as user-specified or
system-learned defaults and preference information. An illustrative
example of a model of current conditions containing user and
environment information is described later with respect to FIG.
8.
[0042] Those skilled in the art will appreciate that computer
systems 220 and 250, as well as their various input and output
devices, are merely illustrative and are not intended to limit the
scope of the present invention. The computer systems may contain
additional components or may lack some illustrated components. For
example, it is possible that the CAM system can be implemented on
the non-portable computer, with the body-mounted computer replaced
by a thin client such as a transmitter/receiver for relaying
information between the body-mounted input and output devices and
the non-portable computer. Alternately, the user may not wear any
devices or computers.
[0043] In addition, the body-mounted computer may be connected to
one or more networks of other devices through wired or wireless
communication means (e.g., wireless RF, a cellular phone or modem,
infrared, physical cable, a docking station, physical contact
between two WPC users, etc.), either with or without support from
other computers such as the computer 250. For example, the
body-mounted computer of a user can make use of output devices in a
smart room, such as a television and stereo when the user is at
home, if the body-mounted computer can transmit information to
those devices via a wireless medium or if a cabled or docking
mechanism is available. Alternately, kiosks or other information
devices can be installed at various locations (e.g., in airports or
at tourist spots) to transmit relevant information to body-mounted
computers within the range of the information device.
[0044] Those skilled in the art will also appreciate that
specialized versions of the body-mounted computer and CAM system
can be created for a variety of purposes. For example, embodiments
of the CAM system can be customized for particular professions to
better enable the system to automatically determine when to create
and recall state fragments for members of those professions.
Alternately, embodiments of the CAM system can be customized for
users that have difficulty in storing and retrieving memories, such
as people with Alzheimer's disease. Those skilled in the art will
appreciate that a variety of such physiological conditions can be
monitored, and that other specialized versions of the system can
similarly be implemented.
[0045] FIG. 3 illustrates an exemplary computer system 300 on which
an embodiment of the CAM system is executing. The computer includes
a memory 330, a CPU 310, a storage device 350, and input/output
devices 320, with the input/output devices including a microphone
322, a video camera 323, a visual display 325, a speaker 326, and
other devices 328. The CAM system includes a State Storage Module
332 and a State Recall Module 334 that are executing in memory, and
can optionally include a User Modeling Module 336 executing in
memory. As various input information is received from the input
devices, the information is forwarded to the executing modules. The
State Storage Module uses the input information to determine when
and how current state information should be stored, and creates and
stores state fragments that include appropriate input information
as well as related supplemental information. The State Recall
Module similarly uses the input information to determine when and
how previously stored state fragments should be presented to the
user, and presents information to the user from stored state
fragments as appropriate. The User Modeling Module uses the input
information to monitor the current state of the user and the
surrounding environment, and maintains a model of the current user
condition.
[0046] In particular, when the State Storage Module determines that
input information reflecting the current state is to be stored, the
module creates a state fragment 340 on the storage device that
includes some or all of the currently available input information.
The input information can include explicit user input to the
computer, sensed user information, and sensed environment
information. The input information can also include information
related to the state of the computer (e.g., battery level or
information about emails stored for the user), as well as
information received from other computers (e.g., from remote
sensors). The module can also receive date and time information as
input from the CPU or from some other source (e.g., from a model of
the current computer condition), and can retrieve stored
information (e.g., user preferences or a default model of the user
condition) from the storage device. A variety of input information
can be stored in the state fragments, including images 342, video
recordings 343, audio recordings 344, and textual information 348.
After creating a state fragment, the State Storage Module also
associates one or more recall tags 345 and annotations 347 with the
stored state fragment. Those skilled in the art will appreciate
that a state fragment can include a variety of other types of
information, and that state fragments can be stored in memory
rather than on the storage device.
[0047] As previously discussed, in some embodiments the user of the
CAM system indicates when a state fragment is to be created, what
current state information is to be stored in the state fragment,
and what additional information such as recall tags and/or
annotations are to be associated with the state fragment. In other
embodiments, the CAM system can automatically determine some or all
of this information. In particular, the State Storage Module may
have access to a means for analyzing information about the current
state and for automatically determining when and how to store
current state information, such as by using the optional State
Storage Rules 356 on the storage device. For example, one of the
rules may indicate that when the State Storage Module receives an
indication from an on-board car computer that the car ignition has
been shut off, then the system can conclude that the user has
parked his car. Another rule may indicate that when it is
determined that the user has parked his car, that the State Storage
Module should then gather 15 seconds of video camera data along
with the current time and GPS coordinates, should store this
information in a state fragment categorized as "car location," and
should query the user for an accompanying annotation. In this
manner, the State Storage Rules can provide a means for the State
Storage Module to determine when and how to store state
fragments.
[0048] In addition to using the State Storage Rules to directly
analyze current state information, the State Storage Module may
also have access to one or more models that reflect raw and derived
information about current conditions. For example, the State
Storage Module may have access to a user model 352 on the storage
device that contains raw and derived state information about the
user and the surrounding environment. The user model may be created
and maintained by the CAM system (e.g., by the User Modeling
Module), or may instead be supplied by another program. Similarly,
the State Storage Module may have access to a computer model 353 on
the storage device that contains raw and derived state information
about the computer (e.g., the current time, the amount of storage
space available on the storage device, an estimate of the expected
time before the batteries supplying the computer need recharging,
and information about emails received). The computer model may also
contain other related information, such as information about
programs executing on the computer. As with the user model, the
computer model may be created and maintained by the CAM system
(e.g., by an optional Computer Modeling Module that is not shown),
or may instead by supplied by other programs (e.g., the operating
system or an external program) or by another computer.
[0049] If the State Storage Module does have access to one or more
models such as the user model and the computer model, the module
may be able to use the model information in conjunction with the
means for automatically determining when and how to store current
state information. For example, the State Storage Rules may only
have a single rule that indicates how to create a state fragment
when it is determined that the user has parked his car, and that
rule may rely on the user model to supply information indicating
when the user has parked the car. In this manner, the State Storage
Rules can, rather than directly processing input information,
instead be directed to more abstract concepts about a derived
current state of the user.
[0050] After the State Storage Module has created and stored one or
more state fragments, the State Recall Module determines when and
how the information stored in the state fragments should be
presented to the user. As previously discussed, in some embodiments
the user of the CAM system indicates that a particular stored state
fragment is to be recalled, and indicates what information from the
state fragment (e.g., all) is to be presented. In other
embodiments, the CAM system can automatically determine situations
in which information from stored state fragments should be
presented to the user. In particular, the State Recall Module may
have access to a means for analyzing information about the current
state and for automatically determining when and how to recall
stored state information, such as by using the optional State
Recall Rules 358 on the storage device. For example, one of the
rules may indicate that when the user is leaving the office for the
day, the State Recall Module should present to the user the video
camera data from the most recent stored state fragment related to
parking the car, but should not automatically present the stored
time and GPS coordinate data from the state fragment. Alternately,
the rule can indicate that only the annotation associated with the
stored state fragment be presented to the user, or that the user
should be queried as to whether the user would like to be presented
with the information from the state fragment. As with the State
Storage Module, the State Recall Module can also make use of
information from other sources, such as the user model and the
computer model, when determining whether and how a stored state
fragment should be recalled.
[0051] When the User Modeling Module receives input information, it
processes the information and uses the processed information to
maintain an updated version of the user model. For example, the
User Modeling Module may have access to the optional User Modeling
Rules 354 on the storage device to use in processing the state
information to maintain the user model. As discussed previously,
the user model may include multiple user condition variables that
reflect both raw sensor data (e.g., the user's heart rate from a
pulse monitor) and derived data reflecting abstracted information
about the user (e.g., a degree of user exertion or agitation based
on the user's heart rate). In addition, previous versions of the
user model can be made available to the User Modeling Module to
assist in the continuing characterization of the user, such as to
track changes over time. As described above, other modules such as
the State Storage Module and the State Recall Module may also
access the user model in order to make automatic determinations
that depend on the current user state.
[0052] It is also possible for one or more application programs 338
to optionally supply input information to one or more of the
modules, such as additional current state information to which the
application programs have access or application-generated derived
information about the current state. In addition, the application
programs can assist the User Modeling Module in modeling the user's
condition by creating new user condition variables (e.g., an
indication of where the user's pupil is directed for an interactive
game program), including those to be used only by that application
program. Similarly, a utility program can supply user condition
information that is useful to a specified subset of application
programs (e.g., to various application programs from a single
vendor or of a certain type).
[0053] Those skilled in the art will appreciate that when
information is being processed and shared between multiple modules
and systems, it is necessary for a context to be shared so that a
semantic understanding of what is represented by information can be
conveyed. For example, merely reporting data for air temperature as
being 50 is insufficient. Not only is it unclear what scale is
being used (e.g., Fahrenheit or Celsius), it is also unclear
exactly what information is being represented (e.g., the air
surrounding the user inside a heated room, or the outside air).
Thus, the modules of the CAM system have a shared context as to the
meaning of input information and user condition variables,
including having consistency among the modules that generate values
of condition variables in models and those that use the generated
values (e.g., the State Storage Module and State Recall Module). In
addition, when information from the CAM system is shared with other
entities (e.g., other CAM systems), sharing of the context with
these other entities enables the information to be useful. In some
embodiments, other systems are designed to share the same context
(e.g., via a published API), while in other embodiments additional
information describing the shared information can be supplied along
with the shared information to establish a shared context.
[0054] Those skilled in the art will also appreciate that, for each
of the modules performing automated processing of current state
information in order to determine when to take actions or to make
conclusions about the current state, there are a variety of
techniques for combining different types of input information and
processing it to generate output information. As indicated above,
some embodiments of the CAM system may use rules such that when a
test portion of a rule is currently true, then the result portion
of the rule is activated or performed (e.g., to cause the value of
a condition variable to be modified, to activate an input device to
record information, or to satisfy the test portion of other rules).
For example, a rule can indicate that if the user is talking or the
surrounding environment is loud, then non-auditory output is
preferable to auditory output. When this first rule was satisfied,
the result can trigger the satisfaction of a second rule, such as a
rule stating that while non-auditory output is currently preferable
then an eyeglass-mounted display device will be used for output.
Alternately, a second rule can state that although non-auditory
output is currently preferable, an earpiece speaker device will be
used for highly sensitive information. Techniques other than using
rules that can be used by other embodiments of the CAM system
include look-up tables, neural networks, expert systems, genetic
algorithms, probabilistic belief networks, etc.
[0055] FIG. 4 is an exemplary flow diagram of an embodiment of the
User-Activated State Storage routine 400. The routine receives
indications from the user when an event of interest is occurring
for which state information should be stored, retrieves a variety
of current state information from input devices, receives
additional information to be associated with the retrieved
information, and stores all of the information as a state fragment
that is available for later retrieval.
[0056] The routine begins at step 405 where an indication is
received from the user to store a state fragment having the current
state of one or more input devices. The indication to create a
state fragment can be made explicitly by the user (e.g., pressing a
hardware button or selecting a displayed menu option), or can
instead be made implicitly by having the user manually activate one
or more input devices (e.g., pointing the video camera in a
direction of interest and activating the recording mechanism). The
current state to be stored can include environment information that
can be detected by a sensor input device, and user-supplied
information on a user input device. After step 405, the routine
proceeds to step 410 where the current information available to the
indicated input devices is captured, and a state fragment is
created that contains the input information. The routine can use
defaults for details such as how long to record information from
the various input devices, or the user can instead specify such
information or manually stop the recording when desired. For input
devices that receive information in a directional manner, such as a
video camera that receives information in the direction that the
video camera is pointing, the system can merely record whatever
information is available to the device and rely on the user to
direct the device appropriately, can remind the user to direct the
device appropriately, or can manipulate the device itself in an
appropriate direction if the system can so manipulate the
device.
[0057] The routine then continues to step 415 to determine other
current state information that should be stored along with the
input information. For example, information about the user or the
user's environment (e.g., from a user model) or information about
the computer (e.g., from a computer model) may be selected as
current state information to be stored in the state fragment. The
selection of other information can be made in a variety of ways,
such as based on explicit user input or instead on user
preferences. The routine next continues to step 420 to receive from
the user an indication of one or more recall tags to be associated
with the state fragment. Those skilled in the art will appreciate
that virtually any type of information can be used as a recall tag,
such as an audio or video recording, text information, a digital
ink representation of handwriting, a still video image or camera
bitmap, etc. In addition, recall tags can represent a variety of
types of information, such as current surroundings (e.g., a photo
of the environment), past surroundings (e.g., a sequential series
of past locations), abstract associations (e.g., a user-generated
label), etc. After step 420, the routine continues to step 425 to
receive from the user an indication of one or more annotations to
be associated with the state fragment. As with the recall tags, a
variety of types of information can be used as annotations. The
routine next continues to step 430 to associate the recall tags and
annotations with the other stored state fragment information. The
routine then continues to step 435 to determine if there are more
state fragments to be created. If so, the routine returns to step
405, and if not the routine continues to step 495 and ends.
[0058] Those skilled in the art will appreciate that additional
types of information can be stored or associated with stored state
fragments, such as category information, an importance level, an
urgency level, a retention time, etc. Similarly, in some
embodiments some of the indicated information may not be included
with the state fragment, such as recall tags or annotations. In
addition, some of information to be included in the stored state
fragment can be indicated by the user, while other information to
be included can be automatically determined by the CAM system. The
routine can also index the stored state fragments in one or more
ways to facilitate later retrieval of the state fragments. For
example, a mapping can be created from the various recall tags to
the stored state fragments with which they are associated so that
those state fragments can be quickly identified when one of those
recall tags is later specified. Alternately, if category
information is available for a stored state fragment, the state
fragment can be associated with those categories to facilitate
later retrieval of state fragments belonging to such categories
(e.g., by creating a category mapping of category types to
corresponding state fragments, or by physically storing a copy of
the state fragment in a location designated for that category).
Those skilled in the art will also appreciate that, while in the
described embodiment information is gathered and stored in the
state fragment in a specified sequential order, in other
embodiments information may be gathered and stored simultaneously
or in a different order.
[0059] FIG. 5 is an exemplary flow diagram of an embodiment of the
User-Activated State Recall routine 500. The routine receives a
user indication to recall a stored state fragment matching one or
more supplied recall tags, identifies stored state fragments which
potentially match the supplied recall tags, and then presents to
the user some or all of the stored state information from the
identified state fragments.
[0060] The routine begins at step 505 where the routine waits to
receive from the user an indication to retrieve a stored state
fragment. After such an indication is received, the routine
continues to step 510 to receive an indication from the user of at
least one recall tag. The routine then continues to step 515 to
identify stored state fragments that match the supplied recall
tags, such as by searching through all stored state fragments or by
using indexing information to identify relevant state fragments.
Those skilled in the art will appreciate that a variety of types of
information can be supplied as recall tags. For example, textual
information can be supplied to match stored textual recall tags.
Alternately, an audio recall tag can be supplied to match either
stored audio recall tags (e.g., by direct comparison of recordings)
or stored textual recall tags (e.g., by performing voice
recognition on the supplied audio recall tag). In addition, rather
than merely matching supplied recall tags to stored recall tags,
alternate embodiments can match supplied recall tags with any
information stored in a state fragment or with other information
associated with a state fragment (e.g., an annotation). Those
skilled in the art will also appreciate that varying degrees of
match between a supplied recall tag and an existing recall tag may
exist. In some embodiments, only perfect matches will be treated by
the routine as being a match, while in other embodiments a match
threshold may be used, and in yet other embodiments all matches
that have a non-zero degree of match may be treated as possible
matches.
[0061] After step 515, the routine continues to step 520 to
determine the number of stored state fragments that were determined
to match the supplied recall tags. If no matches were found, the
routine continues to step 525 to indicate that information to the
user, and then continues to step 570. If more than one match is
found, the routine continues to step 530 to determine whether the
group of possible matching stored state fragments should be limited
to a single state fragment before information is presented to the
user, or if instead information from all of the matching state
fragments should be presented to the user. This determination can
be made in a variety of ways, such as by querying the user or by
using default or preference information. If it is determined that
the number of matches should be further limited, the routine
continues to step 540 to execute subroutine 540 to select a single
stored state fragment. If it is instead determined in step 530 that
the possible matches are not to be further limited, the routine
instead continues to step 533 to prioritize and order the matching
stored state fragments, and then selects the first of the matches
in step 535. Those skilled in the art will appreciate that there
are a variety of ways to prioritize and order the matching state
fragments, such as based on the probability of match between the
supplied recall tags and the stored recall tags, on user-supplied
preferences, on user-supplied relevance ratings for the state
fragments, on retention times for the state fragments, on a
calculated degree of interest to the user, on order of storage,
etc.
[0062] If it is instead determined in step 520 that a single
matching stored state fragment is found, or after steps 535 or 540,
the routine continues to step 545 to replay to the user on
appropriate output devices state information from the selected
state fragment that was previously collected from input devices.
For example, if a stored state fragment includes audio information
recorded from an input microphone and video information recorded
from an input video camera, the audio information can be replayed
on a speaker and the video information can be replayed on a visual
display device. Similarly, textual input information can be
displayed in textual form on a visual display device and/or
converted to audio information to be presented to the user on a
speaker. After step 545, the routine continues to step 550 to
present stored annotation information for the selected state
fragment to the user on appropriate output devices. After step 550,
the routine continues to step 555 to optionally present other state
information stored in the state fragment to the user, such as
textual information from a user model or computer model. A
determination of whether to present this other information can be
made in a variety of ways, such as based on whether such
information is available in the state fragment, on user
preferences, or on explicit user indications. Those skilled in the
art will appreciate that, while in the described embodiment
information from a state fragment is presented to the user in a
specific sequential order, in other embodiments state fragment
information may be presented simultaneously or in a different
order.
[0063] After step 555, the routine then continues to step 560 to
determine if there are more matching stored state fragments that
have not yet been presented to the user. If so, the routine
continues to step 565 to select the next matching stored state
fragment, and then returns to step 545. If it is instead determined
in step 560 that there are no more matching stored state fragments,
the routine continues to step 570 to determine whether to receive
more indications from the user to retrieve stored state fragments.
If so, the routine returns to step 505, and if not the routine ends
at step 595.
[0064] FIG. 6 is an exemplary flow diagram of an embodiment of the
Select Match Based On Additional Information subroutine 540. The
subroutine receives indications of multiple state fragments, and
uses user input to select one of the state fragments whose state
information can then be presented to the user.
[0065] The subroutine begins at step 605 where the subroutine
receives indications of multiple state fragments that match the
previously supplied recall tags. The subroutine then continues to
step 610 to determine what types of additional information should
be used to further limit the group of possibly matching state
fragments to a single state fragment. This determination can be
made in a variety of ways, such as by querying the user or by using
user preference, default information, or patterns of previous user
choice. If it is determined that the annotations associated with
the group of state fragments should be presented to the user, the
subroutine continues to step 615 where the annotations for each
state fragment in the current group are presented to the user on
appropriate output devices. The subroutine then continues to step
620 to receive an indication from the user of at least one of the
state fragments that has been selected based on the presented
information.
[0066] If it was instead determined in step 610 to present other
stored information from the state fragments to the user, the
subroutine continues to step 625 to receive an indication (e.g.,
from the user) of a type of state fragment information to be
presented, such as the time and date that the state fragment was
created. The subroutine then continues to step 630 to present to
the user on appropriate output devices the state information of the
indicated type for each state fragment in the current group. At
step 635, the subroutine then receives an indication of at least
one of the state fragments that has been selected by the user based
on the presented information. After steps 635 or 620, the
subroutine continues to step 640 to remove from the group of
current state fragments those state fragments which were not
selected.
[0067] Alternately, if it was instead determined at step 610 to
perform additional matching among the current group of state
fragments, the subroutine continues to step 645 to receive an
indication (e.g., from the user) of additional information to use
in matching the current state fragments. For example, additional
recall tags may be supplied, or alternately other types of state
information (e.g., annotations or input device information) can be
supplied. The subroutine then continues to step 650 to determine
which of the current state fragments match the additional supplied
information. In step 655, the subroutine determines whether there
is at least one state fragment that matched the additional supplied
information. If not, the subroutine returns to step 610, but if so,
the subroutine continues to step 660 to remove from the group of
current state fragments those state fragments which were not
determined to match the additional supplied information. After
steps 640 or 660, the subroutine continues to step 665 to determine
if a single state fragment remains in the current group. If not,
the subroutine returns to step 610, but if so, the subroutine
continues to step 695 and returns.
[0068] Those skilled in the art will appreciate that, in addition
to the described methods for allowing user determination of a
single state fragment from the group of possible matches, a variety
of alternate methods exist. For example, various automated methods
of selecting a state fragment can be used, such as based on the
state fragment in the group with the highest probability of
matching the previously supplied recall tags. Alternately, the
routine may be able to determine in an automated manner additional
types of matching information to be used in selecting one of the
group of state fragments.
[0069] In addition, those skilled in the art will appreciate that
in addition to creating, storing, and recalling state fragments,
the CAM system can perform a variety of other types of activities.
For example, the CAM system can manipulate state fragments that
have been created in a variety of ways. Some such manipulations are
of an administrative nature, such as deleting state fragments that
are no longer needed (e.g., that have exceeded their retention time
limit). Other manipulations can include modifying state fragments
that are to later be recalled, either based on indications from the
user or based on system-generated indications. For example, such
manipulations can include adding additional information to the
state fragments (e.g., additional recall tags and annotations, or
additional state information that is derived from other stored
state fragment information). Conversely, other manipulations may
modify or remove information stored in or associated with the state
fragment.
[0070] As described above, in some embodiments the determination of
when and how to store and recall state fragments is made based on
user indications, while in other embodiments the determination is
made automatically by the CAM system. When the determination is
made automatically by the CAM system, some embodiments may monitor
the user and the environment in order to gather information about
the current state, and other embodiments may used information from
a model of the user and the environment that is maintained by some
other entity. FIG. 7 illustrates an embodiment of the body-mounted
computer 220 that is executing a Condition-Dependent Output
Supplier (CDOS) system 700 which maintains a model of the current
condition of the user and the user's environment.
[0071] The computer 220 includes a memory 770, a CPU 780, and a
storage device 790. The CDOS 700 system is executing in memory, as
well as one or more distinct application programs 760. The computer
is able to receive input from the flat panel display 230,
microphone 124, other user input devices 222 and 252, user sensor
input devices 226 and 256, environment sensor input devices 228 and
258, and video camera 121 (not shown). The computer is able to
supply output to the flat panel display 230, earpiece speaker 232,
tactile display 236, display 260, speaker 262, olfactory device
264, printer 266, telephone 268, and eyeglass mounted display
234.
[0072] As the body-mounted computer receives various input
information, the information is forwarded to the User
Characterization Module 705 of the CDOS system. The User
Characterization Module monitors the user and the user's
environment in order to create a current user model 710. After the
User Characterization Module has created the user model, the Output
Device Selector Module 715 and the one or more Format Modules
720-278 can then use the model information to determine when and
how to present output information to the user.
[0073] In particular, the User Characterization Module can receive
a variety of types of information, and can use this information to
determine the user's current condition in a variety of ways. These
types of information include explicit user input to the computer,
sensed user information, and sensed environment information. The
User Characterization Module can also receive date and time
information from the CPU or from some other source, and can
retrieve stored information (e.g., user preferences, definitions of
various user-defined groups, or a default model of the user
condition) from the storage device. It is also possible for one or
more of the application programs to optionally supply
application-supplied information 765 to the User Characterization
Module. This information can include any type of user condition
information to which the application program has access, such as
user location or physiological state. In addition, the application
programs can create new user condition variables, including those
to be used only by that application program.
[0074] The various input information can provide current state
information in a variety of ways. For example, user input
information alone can provide significant information about the
user's current condition. If the user is currently supplying input
to the computer via a full-sized keyboard, for instance, it is
likely that the user is engaged in little other physical activity
(e.g., walking), that the user is devoting a significant amount of
attention to the computer system, and that the user would see
information flashed on the display. If the user is instead
generating user input audibly (e.g., through a head-mounted
microphone), that fact may provide less user condition information
since the user can supply such audio information while engaged in a
variety of types of physical activity. Those skilled in the art
will appreciate that there are a wide variety of input devices with
which a user can supply information to the computer system,
including voice recognition devices, traditional qwerty keyboards,
chording keyboards, half qwerty keyboards, dual forearm keyboards,
chest mounted keyboards, handwriting recognition and digital ink
devices, a mouse, a track pad, a digital stylus, a finger or glove
device to capture user movement, pupil tracking devices, a
gyropoint, a trackball, a voice grid device, video cameras (still
and motion), etc.
[0075] In addition to the information received via user input, the
User Characterization Module also uses sensed information about the
user. For example, a variety of sensors can provide information
about the current physiological state of the user, geographical and
spatial information (e.g., location and altitude), and current user
activities. Some devices, such as a microphone, can provide
multiple types of information. For example, if a microphone is
available, the microphone can provide sensed information related to
the user (e.g., detecting that the user is talking, snoring, or
typing) when not actively being used for user input. Other
user-worn body sensors can provide a variety of types of
information, including that from thermometers, sphygmometers, heart
rate sensors, shiver response sensors, skin galvanometry sensors,
eyelid blink sensors, pupil dilation detection sensors, EEG and EKG
sensors, sensors to detect brow furrowing, blood sugar monitors,
etc. In addition, sensors elsewhere in the near environment can
provide information about the user, such as motion detector sensors
(e.g., whether the user is present and is moving), badge readers,
video cameras (including low light, infra-red, and x-ray), remote
microphones, etc. These sensors can be both passive (i.e.,
detecting information generated external to the sensor, such as a
heart beat) or active (i.e., generating a signal to obtain
information, such as sonar or x-rays).
[0076] Stored background information about the user can also be
supplied to the User Characterization Module. Such information
typically includes information about the user that changes at most
infrequently, although it is possible to frequently update the
stored background information to reflect changing conditions. For
example, background information about the user can include
demographic information (e.g., race, gender, age, religion,
birthday, etc.) if it can affect when and how information should be
stored, recalled, or output. User preferences, either explicitly
supplied or learned by the system, can also be stored as background
information. Information about the user's physical or mental
condition which affects the type of information which the user can
perceive and remember, such as blindness, deafness, paralysis, or
mental incapacitation, is also important background information
that allows systems with access to this information to adapt to the
user's capabilities.
[0077] In addition to information related directly to the user, the
User Characterization Module also receives and uses information
related to the environment surrounding the user. For example,
devices such as microphones or motion sensors may be able to detect
whether there are other people near the user and whether the user
is interacting with those people. Sensors can also detect
environmental conditions which may affect the user, such as air
thermometers or Geiger counters. Sensors, either body-mounted or
remote, can also provide information related to a wide variety of
user and environment factors including location, orientation,
speed, direction, distance, and proximity to other locations (e.g.,
GPS and differential GPS devices, orientation tracking devices,
gyroscopes, altimeters, accelerometers, anemometers, pedometers,
compasses, laser or optical range finders, depth gauges, sonar,
etc.). Identity and informational sensors (e.g., bar code readers,
biometric scanners, laser scanners, OCR, badge readers, etc.) and
remote sensors (e.g., home or car alarm systems, remote camera,
national weather service web page, a baby monitor, traffic sensors,
etc.) can also provide relevant environment information.
[0078] In addition to receiving information directly from low-level
sensors, the User Characterization Module can also receive
information from devices which aggregate low-level information into
higher-level data constructs (e.g., face recognizers, gesture
recognition systems, affective/emotion recognizers, etc.). The user
can also explicitly supply information about their current
condition (e.g., "I have a high cognitive load and do not want to
be disturbed" or "I am distracted and will need greater assistance
than normal in recalling current state information"). The User
Characterization Module can also receive current date and time
information in order to both track changes over time and to utilize
information such as the user's stored schedule. Previously-created
models of the user's condition can also be retrieved and used as a
default or to detect changing conditions. Information from the
computer indicating the types of output currently being presented
to the user can provide information about the user's current
activities and cognitive load.
[0079] In some embodiments, multiple CAM or CDOS systems
communicate between themselves, such as via a wireless medium or
when cabled together. This intercommunication can occur
automatically, or at the instruction of one or more of the users of
the communicating systems. When multiple systems communicate, a
variety of types of information can be passed between the systems.
For example, a first CDOS system receiving information from other
CDOS systems can use those other systems as a type of remote sensor
in which information received by the User Characterization Modules
of the other systems is also supplied as input to the User
Characterization Module of the first system. Other systems may also
have access to information about the surrounding environment (e.g.,
a still video camera) that a system does not have. Alternately,
information about the users of the systems can be exchanged and
included in a state fragment about an encounter between the users,
or to facilitate further communication between the systems or
between the users (e.g., notifying one user that another user has a
high cognitive load and does not wish to be disturbed). Multiple
systems can also act as cooperative systems in which one or more
users' systems are shared with other users (e.g., making available
excess computing power or the use of an output device).
[0080] After the User Characterization Module receives one or more
of these types of information, it processes the information and
creates a current model of the user condition which will include
multiple user condition variables (with current values for some or
all of the variables). Once the model of the user condition has
been created and then later updated, older versions of the model
will be made available to the User Characterization Module to
assist in the characterization of the user, such as with changes
over time. The model will also be available to the Output Device
Selector Module to assist with presentation of output information.
Moreover, the model of the user condition can additionally be
stored in a permanent manner, such as on the storage device, if
non-current versions of the user condition model are useful.
Similarly, the User Characterization Module, Output Device Selector
Module, and any Format Modules can be permanently stored before
being executed in memory, and any changes made to the modules while
they are executing can also be saved.
[0081] The model of the current user condition can represent a
variety of types of information. In one embodiment, the User
Characterization Module merely stores the data it receives (even
when it is at a low-level of abstraction) and then allows other
modules to directly use that stored information when making
decisions related to the current state. In an alternate embodiment,
the User Characterization Module uses received low-level data to
generate higher-level representations of the user's observable
activities (e.g., walking, watching a movie in a movie theater,
talking to co-workers at the office, etc.).
[0082] In yet another embodiment, the User Characterization Module
further characterizes the user's condition with respect to
condition variables that are not directly observable. Such
condition variables include the current cognitive load of the user
(indicating amount of attention required for the user's current
activities and thus the ability of the user to devote attention to
the computer), the current degree of interruptibility for the user
(indicating ability to safely interrupt the user), the current
degree of intrusiveness of output on the environment (indicating
impact of output on the surrounding environment), the user's
desired scope of audience for information being output (indicating
how many people should be able to perceive the information), the
user's desired level of privacy for information being output
(indicating the group of people who are allowed to perceive the
information), and the user's desired level of solitude (indicating
the user's current desire to avoid intrusions).
[0083] User condition variables can also represent abstract
principles about the user and the surrounding environment, such as
the user's relationship to other objects, people, or locations
(e.g., being at their desk, being in their office, being near the
drug store, talking to a particular person, etc.). In some
embodiments, CDOS systems can supply information about user
condition variables and their values to other CDOS systems, and
those other CDOS systems can add the user condition variables
and/or values to their model of their user condition if appropriate
(e.g., ambient air temperature, or an emotional state of a CDOS
system's user that is sensed by another CDOS system).
[0084] The CAM system can use information from the user model to
determine how and when to store current state information. For
example, a high-level condition variable can be created that
directly indicates whether the user would like current state
information to be stored in a state fragment. Alternately, the
determination of whether to create a state fragment can be made
based on one or more other high-level condition variables. For
example, if the user's mood is determined to be very happy, the CAM
system may determine to store a state fragment since the user may
wish to remember the environmental factors which may be
contributing to the happy state. Alternately, if the ambient noise
in the surrounding environment is high or the user's cognitive load
is high, an increased amount of state information can be stored in
state fragments since the user may be less likely to perceive and
remember information. In addition, if sufficient storage space is
available, all available input information can be stored in
successive state fragments (e.g., each state fragment representing
5 minutes of time) which are retained for a limited period of time
(e.g., a day) so that the user can later recall any part of the day
which they may not remember.
[0085] In a similar manner, the values for the user condition
variables can also directly impact how and when previously stored
state information should be presented to the user. Thus, a
high-level condition variable can be created that directly
indicates that the user would benefit from receiving previously
stored state information from a state fragment, or that the user
would like to receive such state information for a particular
category or recall tag. Alternately, the determination of whether
and how to recall a stored state fragment can be made based on one
or more other high-level condition variables. For example, when the
user's cognitive load is high or the degree of interruptibility is
low, an indication that stored state fragment information is
available may be presented in a manner that is minimally intrusive
to the user (e.g., on a tactile display using light pressure).
Alternately, the presentation of the information may be deferred if
no appropriate output device is available or if interrupting the
user is not warranted by low-importance or low-urgency information.
When the stored state fragment information is sensitive and others
present are not included in the current desired level of privacy,
the information may be presented on an eyeglass-mounted display, or
the information may be presented via an earpiece speaker when the
scope of audience or intrusiveness on the surrounding environment
dictates that others not perceive the presented information.
Finally, if the user's desired level of solitude indicates that the
user does not want to receive output information (e.g., while
asleep, in the bathroom, involved in an intimate activity, etc.),
presentation of all output information or of all but highly urgent
and important output information may be deferred.
[0086] Those skilled in the art will appreciate that the User
Characterization Module may receive contradictory information
related to one or more aspects of the user condition. For example,
a motion sensor device may indicate that no one else is present in
a room, while a speech recognizer may report that another person is
present. Mediation of such contradictory data can be handled in a
variety of ways. For example, it may be possible to reconcile such
data (e.g., the user is communicating with another person via a
telephone with a loudspeaker). Alternately, the data can reflect
different readings for changing conditions (e.g., ambient air
temperature may have changed quickly after a window was opened).
When data truly conflicts, it may be impossible to reach a
conclusion about a user condition variable, or the value of the
variable may be represented as having varying degrees of
uncertainty or belief. Both particular information sources (e.g.,
sensors) and particular pieces of input information can be
categorized as to their quality and reliability to assist with
mediation or to better model the user condition. In addition, input
information can be time-stamped and otherwise identified to assist
the User Characterization Module.
[0087] Those skilled in the art will also appreciate that a variety
of factors can influence the determination of values for each of
the condition variables, and that the values for the variables can
be stored in a variety of ways (e.g., a number on a scale of 1-100
or 0-255, a probability distribution, a value from a delimited set
of possibilities, a fuzzy logic value, etc.). Factors which can
affect the cognitive load of a user include if the user is talking
(and the volume of the speech), is talking on the phone, physical
movement such as walking or driving, being stationary, being seated
and stationary, ambient light and sound, stress and hunger levels,
a level of rest (e.g., a low level due to a recent lack of sleep),
activity such as reading e-mail or riding a bull, historical data
(e.g., user has low threshold for cognitive load while watching
baseball games), a physical or mental disability, location (e.g.,
at home or therapist's office), presence and frequency of user
input such as keyboard or mouse activity, presentation of output
information to the user, emotional state, explicit indications from
user, etc. Similarly, factors that can affect desired level of
privacy and desired scope of audience include the identity of
others near the user, the proximity of others to the user, explicit
tagging of activities or information (e.g., email in my personal
account is private for only me, while email in my family account is
private for family members), nature of work being performed (e.g.,
balancing a checkbook, playing a computer game, or revising a
business spreadsheet), location, historical data, explicit
indications from user, etc.
[0088] In addition, values for some user condition variables may be
calculated only periodically or only upon specific request for the
value (e.g., computationally intensive variable values such as
those generated by a face recognizer), even if the appropriate
input information is supplied more frequently. Conversely, some
embodiments of the CDOS system may allow the User Characterization
Module to request or retrieve the appropriate input information
needed to calculate one or more user condition variables, thus
performing demand-driven processing. An illustrative example of a
User Characterization Module is described in greater detail with
respect to FIG. 9.
[0089] In some embodiments, CDOS systems can supply to other CDOS
systems various information related to generating the model of the
user condition, and those other CDOS systems can use that model
generation information in addition to or in place of their own
model generation information. For example, if rules are being used
to generate the model of the user condition, one CDOS system can
supply some or all of its rules to other CDOS systems. Similarly,
default and/or specialized sets of model generation information can
be supplied to a CDOS system, either from other CDOS systems or by
loading that information onto the CDOS system. A default set of
rules may be used by a CDOS system until learning by the system
adds or modifies the default rules to better model the user of the
system. Similarly, other programs (e.g., application programs) can
supply rules to the CDOS system, such as rules specific to that
application program. Various specialized sets of rules can also be
supplied. For example, sets of rules may be specialized based on
occupation (e.g., a nurse, a secretary, a field technician, or a
firefighter), gender (e.g., a woman's rules may understand
physiological symptoms related to pregnancy or other
female-specific conditions), age, or any of a variety of other
specialization types.
[0090] After the User Characterization Module has created a model
of the user's current condition, the Output Device Selector Module
and the one or more Format Modules can then use the model to
determine when and how to present output information to the user.
Thus, when the Output Device Selector Module receives output
information to be presented, such as from one of the application
programs or from a CAM system, it uses the current model of the
user condition as well as information about the available output
devices to determine an appropriate output device on which to
present the information to the user. In some embodiments, the
Output Device Selector Module may retrieve information about the
output device characteristics upon initialization, such as from the
storage device. Alternately, the Output Device Selector Module can
instead receive the information directly from the output devices as
they are dynamically configured. The source of the output
information can also supply a description of the information to
assist in selecting where, when and how to present the information
to the user. After an output device has been selected, the Output
Device Selector Module forwards the output information as well as
appropriate output information description factors and user
condition variables to the Format Module for the output device. In
the illustrated embodiment, Format Modules 720 through 728
correspond to the output devices as shown.
[0091] The Output Device Selector Module can select an appropriate
output device for presenting information to the user in a variety
of ways. For example, if the model of the user condition indicates
that auditory output is currently preferable to other forms of
output and the output information can be presented audibly, then
the Output Device Selector Module selects an output device that
supports audible output. Alternately, the value of a desired level
of privacy, desired scope of audience, or current cognitive load
user condition variable may indicate that audible output is
currently preferable.
[0092] In one embodiment, the Output Device Selector Module selects
output devices by first characterizing each of the output devices
relative to selected condition variables, such as cognitive load,
desired level of privacy, desired scope of audience, and
intrusiveness on the environment. For example, an eyeglass-mounted
display may have a high rating for ability to present sensitive
information to only the user, but may have a low rating for lack of
intrusiveness on the user (particularly if the user has a high
cognitive load from another visual activity). Similarly, an
olfactory device which can output various smells may be low on the
intrusiveness scale, but may be useful for presenting only limited
types of output (e.g., a soothing aroma when the user has high
blood pressure and a high pulse). Output devices can also be
characterized on the basis of the user sense (e.g., olfactory or
visual) to which the output information will be presented.
[0093] After the output devices have been characterized on the
basis of the condition variables, the Output Device Selector Module
then selects the one or more output device which are most
appropriate for the user's current condition and for the
information to be output. In some situations, a characterization of
a device relative to a condition variable is dependent on the
circumstances rather than being inherent in the capabilities of a
device. For example, a stereo or a television may have a high
degree of privacy while only the user is in the room, but the
characterization for these devices may change to a low degree of
privacy when others enter the room. In some embodiments, such
devices are represented with a characterization that is a range of
values, with only a single value or a subset of the range selected
at a given time based on the current circumstances.
[0094] In addition to supplying the output information to be
presented, an external entity can also supply information that
describes the output information, such as the relative importance
and urgency (i.e., the degree of deferability, such as time
sensitivity) of the information, as well as the consequences of
ignoring the information. In the same manner that the output
devices can be characterized relative to condition variables, they
can also be characterized relative to such factors in the
description information. For example, an eyeglass-mounted display
and an earpiece speaker with adjustable volume may both be
highly-rated with respect to their ability to present important
information that has a high consequence of being ignored. The
earpiece speaker may have a wide range of ratings for these
factors, however, since it is also able to present low importance
information (e.g., at a low audio volume which can be easily
ignored by the user if the user so chooses). Conversely, the
eyeglass-mounted display may not be able to unobtrusively present
visual information, and thus may have a small range of ratings for
this factor. Thus, after the Output Device Selector Module receives
the information to be output and optionally receives a description
of the information, the Output Device Selector Module then uses the
model of the user condition to determine which output device (if
any) to use to present the information to the user, and a
corresponding Format Module for that device determines the
appropriate format with which to present the information to the
user.
[0095] In one embodiment, the Output Device Selector Module
includes a characterization of each output device available to the
CDOS system relative to the user condition variables of cognitive
load, desired level of privacy, desired scope of audience, and
desired level of intrusiveness on others, as well as to output
information description factors of relative level of importance,
deferability, and consequence of ignoring. The one or more devices
which best match the current user condition and the current output
information will be selected, including using user preferences to
select between different devices. Those skilled in the art will
appreciate that the Output Device Selector Module can determine an
appropriate output device in a variety of other ways, including
receiving a direct specification from the entity supplying the
output information, selecting the device with the widest range of
capabilities relative to the type of information to be output, etc.
In addition, a defined API (application program interface) can be
designed between external entities such as application programs and
the CDOS system. The defined API will allow application programs to
supply information to User Characterization Modules, extract and
add information to the model of the user condition, and supply
output information and description information to Output Device
Selector Modules. An illustrative example of an Output Device
Selector Module is described in greater detail with respect to FIG.
10.
[0096] After the Output Device Selector Module supplies output
information to a Format Module, the Format Module formats the
output information for presentation, with the formatting based in
part on the information presentation capabilities of the output
device. For example, the output device may be able to output
information to more than one user sense, in more than one way, and
with varying degrees of amplitude or style (e.g., flashing text or
enlarged icons). The Format Module selects an appropriate method of
formatting the information, such as to present the information to
only the appropriate audience or with the appropriate level of
intrusiveness, and then sends the information to its corresponding
output device for display. The Output Device Selector Module will
also inform the User Characterization Module when output is to take
place so that the model of the user condition can be updated
accordingly.
[0097] While information to be presented to the user will often be
generated by an entity outside the CDOS system, the CDOS system may
also generate information to be presented to the user (e.g., an
indication of low battery power, or of an error when adding a rule
to the User Characterization Module). In addition, in some
embodiments external entities, such as an application program or
the CAM system, can directly access the model of the user condition
and make their own determination as to when, where and how to
present output information (i.e., bypassing the Output Device
Selector Module and/or the Format Modules). Thus, if the modeled
user condition indicates that particular output information should
not currently be presented to a user, the external entity can
postpone or cancel the presentation of the output information
without ever supplying the output information to the CDOS system.
It may also be possible to configure the CDOS system to
automatically notify the external entities of the values of one or
more user condition variables, such as by pushing that information
to the external entities when changes occur in the values or by
periodically notifying the external entities of the current
values.
[0098] Those skilled in the art will appreciate that the Format
Modules may communicate with their corresponding output devices in
a variety of ways, and that the body-mounted computer in the CDOS
system may contain additional components or may lack some
illustrated components. For example, there may not be a one-to-one
mapping between Format Modules and output devices, functionality
performed by the Output Device Selector Module and Format Modules
may be incorporated together, and the creation of the model of the
user condition may be performed by a different system than that
which uses the information to present output information. There may
also be multiple User Characterization or Output Device Selector
Modules, such as one User Characterization Module for each relevant
high-level condition variable. Alternately, external entities such
as the application programs can add their own User
Characterization, Output Device Selector or Format Modules, or can
directly access the model of the user condition in order to perform
presentation of output information. Accordingly, the present
invention may be practiced with other computer system
configurations.
[0099] In addition, those skilled in the art will appreciate that
CAM and CDOS systems can be simultaneously executing, either on the
same computer or on different computers, and can communicate in a
variety of ways. In some embodiments, the CAM system may merely use
the user model created by the CDOS system, while in other
embodiments the systems may exchange a variety of types of
information. For example, the CAM system can forward state
information from a stored state fragment to the Output Device
Selector Module and allow that module to determine how best to
present the information to the user. In other embodiments, the CDOS
system or User Characterization Module may be a module of the CAM
system (e.g., the User Modeling Module), while in other embodiments
the systems may be separate.
[0100] FIG. 8 is an illustrative example of a Model of User
Condition 710. As is shown, the model reflects the condition of
user X at time 14:22 hours on the displayed date. The illustrative
model of the user condition includes a variety of user condition
variables at different levels of abstraction, including low-level
information directly from user sensors as well as higher-level
abstract variables with characterized values that reflect a user's
current physical and mental states. Historical and time-sensitive
information can also be included, as shown by the variable
illustrating the last user input performed by user X.
[0101] Intermediate-level variables included in the model can be
calculated from low-level input information such as sensor values.
For example, the speed of the user can be calculated directly by a
sensor such as a pedometer, or can be calculated indirectly via
information over time from a GPS sensor. In addition, the Speed
variable indicates that additional information can be included in
the user model for each variable. In the case of the Speed
variable, uncertainty about the exact value of the variable is
demonstrated. Other calculated condition variables include an
indication that the user is located in their office, is near their
desk, and that there are no other people physically nearby. These
factors can be determined in a variety of ways, such as via a
motion sensor device located on the desk that is tracking the user
and the absence of other individuals, or by the lack of any sounds
from any other people via one or more microphones.
[0102] Higher-level condition variables can also be calculated,
such as the user's current physical activities, the current user
cognitive load, the desired level of privacy, and the desired scope
of audience. Information from the microphone or directly from the
cellular phone can indicate that the user is currently talking on
their cellular phone, and the speed and motion sensor data can
indicate that the user is walking. Since the user remains near his
desk even though he is walking, the system can deduce that the user
is pacing about his office or is walking on a treadmill (not
shown). The User Activity variable demonstrates that variables can
have multiple values, and that information such as a degree of
belief or certainty in the value for a variable can be added and
used by the system.
[0103] The Cognitive Load variable indicates a score of 77 out of
100, thus indicating a relatively high cognitive load due to the
combination of the user walking and talking on the phone. Since it
is unlikely that information presented by the system will be
desired to be perceptible by the person on the other end of the
phone, the desired Scope Of Audience variable indicates that only
the user is currently appropriate to receive output information.
Since the User Characterization Module was able to identify the
other person on the phone as Doug Smith, an executive level
colleague at user X's company (e.g., by voice recognition or the
use of that person's name), the desired Level Of Privacy variable
indicates that if information is presented in a manner such that
the other person can receive it (e.g., through an external
speaker), general information about the company as well as
executive-level sensitive information can be presented. Note that
although low-level sensors such as a motion detector may have
indicated that there are no other people physically nearby, when it
was determined that the user was talking on a phone, additional
information was added to the Nearby People variable to indicate
that someone is within audio perception of the user.
[0104] The remaining displayed portions of the user condition model
indicate that user preference information and externally supplied
information can be included in the user condition model. For
example, the Application X-Factor I variable has been supplied by
application X, as well as a value for the variable. In this case,
the value is a normal probability distribution with a mean of 23
and a standard deviation of 3. In addition, previously supplied
user preference information can indicate which output devices and
which output formats are preferred by the user. Alternately, the
system can have automatically learned these preferences over time
by observing user reactions to various outputs, as well as from
explicit suggestions and overrides by the user. Those skilled in
the art will appreciate that the illustrated user condition model
is merely illustrative and is not intended to limit the scope of
the present invention. The model may contain additional variables
or may lack some illustrated variables, or may be represented
without explicit condition variables at all.
[0105] FIG. 9 is an illustrative example of User Characterization
Module 705. As is shown, the illustrated User Characterization
Module is for user X and it includes a variety of IF-THEN rules.
User condition variables are shown with angle brackets surrounding
them, with some user condition variables (e.g.,
Speakerphone.Status) not shown in the illustrative model of user
condition 710 in FIG. 8. In addition to the IF-THEN rules,
WHILE-THEN rules are also shown, as well as an application-specific
rule (i.e., the APPX: rule) added by an external application. The
illustrative User Characterization Module also indicates that the
results portion of the rules (shown after the THEN statements) can
set or modify the values of condition variables, such as by
absolute or percentage numerical amounts, and can indicate degrees
of belief or uncertainty in values. Groups of people are shown in
square brackets (e.g., Company Executives), and asterisks are
wild-card characters that can match any information.
[0106] As mentioned previously, receiving input related to one user
condition variable can cause multiple changes to propagate through
the set of rules. For example, if input is received that indicates
that the user condition variable
Desktop.Motion.Sensor.Human.Movement is true and the User Activity
variable value indicates that user is seated, one of the rules
shown indicates that the Nearby People variable will be modified
(if necessary) to indicate that an "Unidentified Person" is
physically nearby. Modifying the Nearby People variable can then
affect the Level Of Privacy or Scope Of Audience user condition
variables as shown by other rules. Those skilled in the art will
appreciate that the illustrated User Characterization Module is
merely illustrative and is not intended to limit the scope of the
present invention. The model may contain additional rules, may lack
some illustrated rules, or may be implemented without using rules
at all. In addition, the test and/or results portions of rules can
be implemented as invokable functions, including those provided by
external entities such as application programs. Those skilled in
the art will appreciate that the State Storage Rules 356 and State
Recall Rules 358 discussed in FIG. 3 can use a format similar to
that of the rules illustrated for the User Characterization
Module.
[0107] FIG. 10 is an illustrative example of Output Device Selector
Module 715. As is shown, the module is for user X and it maps each
available output device to ratings for selected user condition
variables and output information description factors. As is shown,
some output devices which are available at times (e.g., pager 1002,
cellular telephone 1004, and car radio 1006) are not currently
available. In addition, earpiece speaker 232 may not currently be
able to receive output information if it is already in use (e.g.,
the user is listening to music). Alternately, new output
information can preempt the current use of the earpiece speaker if
necessary, or can instead share the use of the output device (e.g.,
outputting music to one ear and other information to the other ear
if the earpiece speaker is part of headphones).
[0108] As is shown, the various output devices are rated with
single values or a range of values for each factor. While textual
values are used, those skilled in the art will appreciate that
numerical or other types of rating systems can be used. In the
illustrated embodiment, ranges may illustrate the device
capabilities in different situations, with the ranges being
restricted in any particular situation. For example, the earpiece
speaker can accommodate when the user has a very low cognitive load
by adjusting the volume to be slightly louder than the ambient
environment. Alternately, even if the user has a high cognitive
load, the earpiece speaker can interrupt the user if necessary for
urgent information by using very loud volumes or distinctive tones.
In addition, the ratings can be adjusted to reflect the specific
situation of this user. For example, since the speaker 262 is
located on the user's desk at work and other employees can
frequently or always hear the speaker, the value for the desired
Level Of Privacy may indicate that only business information be
presented via the speaker. Alternately, the system can present
information by sending it to the cellular telephone if the
information is highly sensitive or it is important to interrupt the
user. However, if others are present around the user, frequent use
of the cellular telephone can be highly intrusive to them
(particularly in environments such as a lecture or a movie).
[0109] Those skilled in the art will appreciate that the
illustrated Output Device Selector Module is merely illustrative
and is not intended to limit the scope of the present invention.
The module may contain additional user condition variables and
output information description factors, may lack some illustrated
user condition variables and output information description
factors, or may select output devices on which to present output
information in an entirely different manner. For example, the
output devices can be rated on the basis of their ability to output
different types of stored state information, or on the basis of
their ability to output state information for stored state
fragments of different categories or degree of interest to the
user. In addition, some embodiments of the Output Device Selector
Module may include specific logic, such as IF-THEN rules, to be
used in conjunction with the mapping of output devices as
shown.
[0110] FIG. 11 is an exemplary flow diagram of an embodiment of the
User Characterization Routine 1100. The User Characterization
Routine retrieves stored information related to the user, including
a default model of the user condition, receives various types of
input information related to the user or the user's environment,
updates the model of the user condition to reflect the new
information, and periodically updates the model if no information
has been received within a prescribed time. The routine begins at
step 1105 where stored information for the user is retrieved,
including a set of characterization rules to be used by the
routine. The routine then creates a default model of the user
condition, such as directly from stored information or by applying
the characterization rules to default user information that is
available. The routine then continues to step 1110 to set a timer,
and continues to step 1115 to either receive input information or
to receive a notification that the timer has expired.
[0111] The routine continues to step 1120 to determine if input
information was received. If so, the routine continues to step 1125
to determine if the information received was information input to
the computer by the user. If so, the routine continues to step 1130
to determine if the user input indicates that the user condition
should be modified, such as by setting a user preference or
explicitly changing the value of a user condition variable. If so,
the routine continues to step 1135 to satisfy the user request, and
then returns to step 1110. If it was instead determined in step
1130 that the user input was not directed to the User
Characterization Module, the routine continues to step 1140 to
forward the user input information to the appropriate destination
(e.g., an application program).
[0112] After step 1140, or if it was determined in step 1120 that
the timer had expired or in step 1125 that the information received
was not user input, the routine continues to step 1145 to execute
the Characterize User Subroutine to update the model of the current
user condition. After step 1145, the routine continues to step 1150
to store the updated user condition model, and then continues to
step 1155 to update the characterization rules if necessary. The
characterization rules can be updated in a variety of situations,
such as if an external entity (e.g., an application) explicitly
adds a new characterization rule or if the routine monitors the
user's behavior and reactions in an attempt to learn more
appropriate characterization rules. After step 1155, the routine
continues to step 1160 to determine if there is more information to
receive. If so, the routine returns to step 1110, and if not, the
routine ends at step 1195.
[0113] FIG. 12 is an exemplary flow diagram of an embodiment of the
Characterize User Subroutine 1145. The subroutine is executed when
information is received related to the user or the user's
environment, or when a timer has expired indicating that no
information has been received for a specified period of time. When
no information has been received for a period of time, the model of
the user's current condition may need to be updated so that
time-sensitive information can be updated in the model of the user
condition. The subroutine begins at step 1205 where the current
model of the user condition is retrieved. The subroutine then
continues to step 1210 to retrieve the current date and time. In
step 1215, the subroutine determines whether information was
received or if the timer has expired. If the timer has expired, the
subroutine continues to step 1220 to examiner user condition
variables that represent time-sensitive information or historical
data and updates them if necessary. The subroutine then continues
to step 1225 to determine if the current date and time trigger any
characterization rules, and if so, the changes from these triggered
rules are propagated through the set of rules.
[0114] If it was instead determined in step 1215 that information
to be processed was received, the subroutine continues to step 1230
to determine if a new user condition variable has been defined,
such as by an application program, and if so continues to step
1250. If a new user condition variable has not been defined,
however, the subroutine continues to step 1235 to determine if a
new user characterization rule is being added, such as by an
application program. If so, the subroutine continues to step 1240
to add the new characterization rule, determine if current values
for any user condition variables trigger the rule, and if so
propagates any changes from the triggered rules through the set of
rules. If it was instead determined in step 1235 that a new
characterization rule is not being defined, the subroutine
continues to step 1245 to determine if the current input
information or the current date and time trigger any rules, and if
so, changes from those triggered rules are propagated throughout
the set of rules. In addition to information received directly from
the user, sensors, or application programs, this input information
can also be a notification from the Output Device Selector that
indicates output information is currently being presented to the
user.
[0115] After steps 1225, 1230, 1240, or 1245, the subroutine
continues to step 1250 to store any changes in user condition
variables and their values, as well as the new date and time, in an
updated model of the user condition. The subroutine then continues
to step 1295 and returns. Those skilled in the art will appreciate
that a variety of types of information related to the user and the
user's environment can be received, and that the User
Characterization Routine and the Characterize User Subroutine can
process this information in a variety of ways, including other than
with sets of IF-THEN rules.
[0116] FIG. 13 is an exemplary flow diagram of an embodiment of the
Output Device Selector Routine 1300. The Output Device Selector
Routine receives output information to be presented to the user,
retrieves current characterized information about the user from the
model of the user condition, determines whether the output
information should be presented to the user at this time and if so
on which output device and in what format, and then notifies the
User Characterization Module when output information is presented
to the user. The routine begins at step 1305 where output
information to be presented to the user is received or an
indication that a timer has expired occurs. The routine continues
to step 1310 to determine if a timer has expired. When output
information cannot be currently presented to the user (e.g., no
satisfactory output device is available or presentation to the user
can be dangerous or inappropriate), the presentation is deferred
and a timer is set to indicate when to review presenting the
information. Thus, if it is determined in step 1310 that a timer
has expired, the routine continues to step 1315 to retrieve the
deferred output information for the timer, as well as any
description information for the deferred output information. If it
is instead determined in step 1310 that new output information to
be presented has been received, the routine continues to step 1320
where description information for the output information is
optionally received.
[0117] After steps 1315 or 1320, the routine continues to step 1325
to retrieve relevant information from the current model of the user
condition. The routine then continues to step 1330 to determine
whether to currently present the output information to the user. In
the illustrated embodiment, this determination is made using the
user condition variables of cognitive load, desired level of
privacy, and desired scope of audience. In addition, available
description information which indicates the importance and the
deferability of the output information and the consequences of the
user ignoring or not receiving the output information are
considered, as is any user preference information. Current values
for these user condition variables and description factors, as well
as whether available output devices can support the necessary
formatting of information (e.g., presenting information to the
appropriate scope of audience or at the appropriate level of
intrusiveness for the user's cognitive load), are thus used in the
determination. Those skilled in the art will appreciate that other
factors can be used for this determination or that the
determination can be made in other ways.
[0118] The routine then continues to step 1335 to determine whether
the presentation of the information is to be deferred or not. If
the presentation is to be deferred, the routine continues to step
1340 to store the output information as well as its description
information, and to set a timer for the information at which time
the presentation of the output information will be reconsidered. If
it is instead determined in step 1335 that the information
presentation is not to be deferred, the routine continues to step
1345 where an available output device is selected. In the
illustrated embodiment, the output device whose information display
capabilities and ratings best match the user condition variables
and description information factors of interest is chosen. The
routine then continues to step 1350 to execute the Format And
Present Output Information Subroutine, and then continues to step
1355 to notify the User Characterization Module of the presentation
of the output information. After step 1340 or step 1355, the
routine continues to step 1360 to determine if there are currently
timers set or there is more output information to be received. If
so, the routine returns to step 1305, and if not the routine ends
at step 1395.
[0119] FIG. 14 is an exemplary flow diagram of an embodiment of the
Format And Present Output Information Subroutine 850. The
subroutine receives output information to be presented and its
description information, receives relevant user condition variables
and user preference information, selects a user sense to which the
output information will be presented (if the output device supports
more than one), selects appropriate formatting with which to
present the output information, and presents the output information
to the user. The subroutine begins at step 1405 where output
information is received, as well as the description information
factors, user condition variables, and relevant user preference
information. The subroutine continues at step 1410 to select a user
sense that is supported by the selected output device.
[0120] In step 1415, the subroutine selects formatting for the
output information that is appropriate for the user condition
variables, output information description, and user preferences.
Those skilled in the art will appreciate the formatting of the
output information will vary with each user sense (e.g., adjusting
volume for the audio sense and adjusting pressure for the tactile
sense), as well as with the specific output device. After the
formatting for the output information is selected, the subroutine
continues to step 1420 to present the output information to the
user with the selected formatting. If the Scope Of Audience and
Level of Privacy user condition variables indicate that the
information can be presented to other people currently present and
the selected output device supports such presentation, the
information will also be presented to these other people. After
step 1420, the subroutine continues to step 1495 and returns.
[0121] Those skilled in the art will appreciate that the selection
of an output device and the formatting of the output information
for that device can be performed in a variety of ways. For example,
other user condition variables and description information factors
can be used, or the selection can be made without resort to such
information. For example, in one embodiment, the user can
explicitly indicate the output device and formatting desired for
some or all pieces of output information (e.g., in response to an
notification from the system), or another entity (e.g., an
application program supplying the output information) can
explicitly designate the output device and/or formatting.
[0122] FIG. 15 is an exemplary flow diagram of an embodiment of the
System-Activated State Storage routine 1500. The routine
automatically determines when an event of interest is occurring for
which state information should be stored, retrieves a variety of
current state information from input devices, determines additional
information to be associated with the retrieved information, and
stores the information as a state fragment that is available for
later retrieval.
[0123] The routine begins at step 1505 where the subroutine
Determine Whether To Store Current State Of Input Devices, User
Model, and Computer Model is executed to determine if current state
information should be stored in a state fragment. The routine then
continues to step 1510 to determine if a state fragment is to be
created. If not, the routine returns to step 1505, and if so, the
routine continues to step 1520. At step 1520, the routine executes
the Create State Fragment subroutine to create a state fragment
having the appropriate current state information and additional
information (e.g., recall tags and annotations). After step 1520,
the routine continues to step 1525 to determine whether to create
additional state fragments. If so, the routine returns to step
1505, and if not, the routine continues to step 1595 and ends.
[0124] FIG. 16 is an exemplary flow diagram of an embodiment of the
Determine Whether To Store Current State Of Input Devices, User
Model, and Computer Model subroutine 1505. The subroutine
determines if current state information should be stored in a state
fragment for any of multiple reasons. The subroutine begins at step
1605 where it is determined whether state fragments are being
continuously stored so as to maintain a continuous log of events
occurring in the environment surrounding the user. If not, the
subroutine continues to step 1610 to determine whether state
fragments are being periodically created (e.g., based on a timer
set for a specified period of time), and if so, whether it is time
to now create another state fragment. If not, the subroutine
continues to step 1615 to determine whether a state fragment was
previously scheduled to be created at this time (e.g., to record a
scheduled event). If not, the subroutine continues to step
1620.
[0125] At step 1620, the subroutine retrieves the current version
of an available user model, and then continues to step 1625 to
retrieve the current version of an available computer model. The
subroutine then continues to step 1630 to retrieve the current
version of an available set of State Storage Rules. After step
1630, the subroutine continues to step 1635 to retrieve the input
information available to the current set of input devices. The
subroutine then continues to step 1640 to apply the State Storage
Rules to the current state information from the user model,
computer model, and input devices in order to determine whether an
event of interest is currently occurring which warrants the
creation of a state fragment. Those skilled in the art will
appreciate that there are a variety of ways to use rules to
determine when an event of interest is occurring, as well as a
variety of other ways to make such a determination.
[0126] The subroutine then continues to step 1645 to determine
whether it was decided to create a state fragment that stores
current state information. If so, or if any of steps 1605, 1610, or
1615 were determined to be yes, the subroutine continues to step
1650 to indicate that a state fragment is to be created. If it is
instead determined in step 1645 that a state fragment is not to be
created, the subroutine continues instead to step 1647 to indicate
that a state fragment is not to be created. After steps 1647 or
1650, the subroutine continues to step 1695 and returns.
[0127] FIG. 17 is an exemplary flow diagram of an embodiment of the
Create State Fragment subroutine 1520. The subroutine automatically
determines the appropriate current state information to be stored
in the state fragment to be created, determines the appropriate
additional information to be associated with the state fragment,
and then creates the state fragment. The subroutine begins at step
1705 where it retrieves the input information available to the
current set of input devices. The subroutine then continues to step
1710 to retrieve the current version of an available set of State
Storage Rules. The subroutine next continues to step 1715 to
retrieve the current version of an available user model, and then
to step 1720 to retrieve the current version of an available
computer model.
[0128] The subroutine next continues to step 1722 to apply the
State Storage Rules to the current state information from the user
model, computer model, and input devices in order to determine what
information should be stored in the state fragment to be created
(e.g., information about the event of interest that triggered the
creation of the state fragment). As with other state fragments,
information to be stored can include input information received
from one or more input devices as well as information from other
sources such as available user and computer models. In some
embodiments, the stored state fragment can include all current
state information which is available, thus capturing a snapshot of
the entire current state. Those skilled in the art will appreciate
that the appropriate information to be stored can be determined in
ways other than using the State Storage Rules. For example, details
about what information is to be included in the state fragment may
be specified along with the information that triggers the creation
of the state fragment, such as when creation of a state fragment
including specified types of current state information is scheduled
for the current time. Alternately, the details about what
information is to be included in the state fragment may be
determined in a variety of other ways, such as by using user
preference or default information.
[0129] After step 1722, the subroutine continues to step 1725 to
use the State Storage Rules to generate one or more appropriate
recall tags to be associated with the state fragment to be created.
The subroutine then continues to step 1730 to use the State Storage
Rules to generate one or more annotations to be associated with the
state fragment to be created. In step 1735, the subroutine next
uses the State Storage Rules to determine a retention time limit
for the state fragment to be created, and in step 1740 uses the
Rules to determine an importance level for the state fragment.
Those skilled in the art will appreciate that the recall tags,
annotations, retention time limit, and importance level can also be
generated in a variety of ways. For example, derived values for
user condition variables in the user model can be used as recall
tags or annotations. In addition, those skilled in the art will
appreciate that a variety of additional types of information (e.g.,
an urgency level) can be generated for the state fragment, and that
alternate embodiments may not generate some or all of the described
types of information for state fragments being created. Moreover,
some embodiments may have multiple sets of rules, such as separate
sets of rules for determining when a state fragment is to be
created, for determining the types of state information to be
included in the state fragment, for generating recall tags, for
generating annotations, and for generating other types of
information to be included in or associated with the state
fragment.
[0130] After step 1740, the subroutine continues to step 1745 to
store the generated and determined information together as a new
state fragment. The subroutine then continues to step 1750 to
categorize the type of created state fragment. In some embodiments,
this category information can be stored in or associated with the
state fragment, while in other embodiments the category association
may be indicated in other ways (e.g., by storing a copy of or a
pointer to the state fragment in a location associated with the
category). The subroutine then continues to step 1795 and
returns.
[0131] FIGS. 18A and 18B are exemplary flow diagrams of an
embodiment of the System-Activated State Recall routine 1800. The
routine automatically determines when an event of interest is
occurring such that state information from a stored state fragment
would be of interest to the user, identifies one or more such state
fragments, and then presents to the user some or all of the stored
state information from the identified state fragments.
[0132] The routine begins at step 1805 where it retrieves the
current version of an available set of State Recall Rules. The
routine next continues to step 1810 to retrieve the current version
of an available user model, and then to step 1815 to retrieve the
current version of an available computer model. The routine then
continues to step 1820 to retrieve indications of the current
stored state fragments. In step 1825, the routine then deletes the
stored state fragments that have exceeded their retention time
limits. Those skilled in the art will appreciate that deletion of
such state fragments can be performed in a variety of ways, or that
such state fragments could instead be archived or modified so as to
indicate that they have expired. For example, the State Storage
Routine can instead identify and delete such stored state
fragments, either in addition to or instead of the State Recall
Routine. Alternately, an entirely separate routine (e.g., a garbage
collection routine) can perform this function.
[0133] The routine next continues to step 1830 to use the State
Recall Rules to determine stored state fragments that may be of
interest to the user based on the current state information. Those
skilled in the art will appreciate that there are a variety of ways
to use rules to make such a determination. For example, the Rules
can determine whether an event of interest is occurring, and then
determine whether any stored state fragments are related to the
current event of interest. Those skilled in the art will also
appreciate that there are a variety of other ways to make such a
determination rather than using rules. The routine then continues
to step 1835 or to determine whether any stored state fragments
were determined to be of current interest. If so, the routine
continues to step 1840 to prioritize the determined stored state
fragments based on their importance levels. Those skilled in the
art will appreciate that the stored state fragments can alternately
be prioritized in a variety of other ways, such as based on a
probability that the state fragment is currently of interest, on a
degree of match with the rules, on the recency of creation of the
state fragment, etc.
[0134] In steps 1845 through 1880, the routine next presents stored
information of interest from the identified state fragments to the
user. In particular, after step 1840 the routine continues to step
1845 to present to the user on appropriate output devices a summary
of the identified state fragments in the order of their priority. A
variety of types of information can be used as a summary, such as
annotations, recall tags, time of creation, or other information
stored in the state fragments. The routine then continues to step
1850 to determine whether an indication is received from the user
to present additional information for one or more of the state
fragments. If so, the routine continues to step 1857 to receive the
user indication, and then to step 1860 to determine whether the
user indicated that they wish to receive additional stored
information from one or more of the summarized stored state
fragments. If so, the routine continues to step 1862 to replay
additional stored information from the indicated state fragments to
the user on appropriate output devices. The types of additional
information to be presented can be determined in a variety of ways,
such as based on explicit user indication, based on user
preferences or defaults, or instead all stored information can be
presented.
[0135] If it was instead determined in step 1860 that the user did
not indicate one or more stored state fragments, the routine
continues to step 1865 to determine whether the user indicated a
category of state fragments for which to receive additional state
information. If so, the routine in step 1867 determines the state
fragments of the identified category, and then presents additional
stored information for those state fragments to the user on
appropriate output devices. If it was instead determined in step
1865 that the user did not indicate a category, the routine
continues to step 1870 to determine if the user indicated an
importance level of state fragments for which to receive additional
stored information. If so, the routine continues to step 1872 to
determine the state fragments having the indicated importance
level, and then presents additional stored information for those
state fragments to the user on appropriate output devices. If it
was instead determined in step 1870 that the user did not indicate
an importance level, the routine continues to step 1875 to
determine if the user indicated a specific other type of stored
information from the state fragments to be presented. If so, the
routine continues to step 1877 to retrieve the indicated type of
stored information from the state fragments, and then presents to
the user on appropriate output devices the retrieved
information.
[0136] If it was instead determined in step 1875 that the user did
not indicate a specific information type, or after steps 1862,
1867, 1872, or 1877, the routine continues to step 1880 to
determine if there are more user indications to receive. If so, the
routine returns to step 1857. If it was instead determined in step
1880 that there are not more user indications, or if it was
determined in steps 1835 or 1850 that there were not any stored
state fragments or that no indications were received from the user,
the routine continues to step 1885 to determine whether additional
state fragments should be recalled. If so, the routine returns to
step 1805, and if not the routine ends in step 1895.
[0137] Those skilled in the art will appreciate that in alternate
embodiments, state fragment information can be presented to the
user without any explicit user indications in a variety of ways,
such as by presenting all of the stored state information for each
of the identified state fragments in order of priority to the user,
by presenting a determined set of the stored state information for
the state fragment with the highest priority to the user, by
presenting based on the order created or the proximity to current
location, etc. Conversely, the user can be queried before any
information is presented. Those skilled in the art will also
appreciate that a variety of other types of indications can be
received from the user.
[0138] As discussed above, state fragments can be created based
either on explicit user indications or on system-generated
indications, and previously stored state fragments can be presented
to the user based either on explicit user indications or on
system-generated indications. Those skilled in the art will
appreciate that in some embodiments these two types of state
fragments will be treated separately such that user-created state
fragments will be recalled only by explicit user indications, and
similarly that system-created state fragments will be recalled only
by system-generated indications. In alternate embodiments, these
two types of state fragments will be treated interchangeably such
that user-created state fragments can be recalled by
system-generated indications and system-created state fragments can
be recalled by user-generated indications. Those skilled in the art
will also appreciate that in some embodiments only one of the two
types of ways of creating state fragments may be available, and
that in other embodiments only one of the two types of ways of
recalling state fragments may be available.
[0139] From the foregoing it will be appreciated that, although
specific embodiments of the invention have been described herein
for purposes of illustration, various modifications may be made
without deviating from the spirit and scope of the invention.
Accordingly, the invention is not limited except as by the appended
claims.
* * * * *